Multiple input, multiple output communications systems

ABSTRACT

Embodiments of the present invention include systems and methods for optimizing the transmitter and receiver weights of a MIMO system. In one embodiment, the weights are optimized to create and steer beam nulls, such that each transmitted signal is substantially decoupled from all other signals between a MIMO transmitter a MIMO receiver. In another embodiment, the weights are selected such that, the signal strength of each weighted signal transmitted through a communications channel along a respective signal path is substantially equivalent, but for which the weighting vectors are not necessarily orthogonal. In a further embodiment, each transmitted signal is coupled only between its own transmitter and receiver antennas with a gain, or eigenvalue, that is a consequence of the weights, and which is bounded to within a desired range of values while at the same time the weighing vectors are orthogonal. Embodiments employing various decomposition techniques are also provided.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a division of U.S. patent application Ser. No.11/469,075, filed on Aug. 31, 2006, now issued as U.S. Pat. No.7,822,141, which, in turn, is a continuation of U.S. patent applicationSer. No. 10/954,429, filed on Sep. 30, 2004, now issued as U.S. Pat. No.7,548,592, which, in turn, is a continuation-in-part of U.S. patentapplication Ser. No. 10/884,633, filed on Jul. 2, 2004, now issued asU.S. Pat. No. 7,738,595, the disclosures of which are herebyincorporated by reference in their entirety.

FIELD OF THE INVENTION

The present invention is generally related to wireless communicationsystems, and more particularly to improved systems and methods fortransmission and reception of multiple data streams in a multiple-input,multiple-output communications channel.

BACKGROUND OF THE INVENTION

In wireless communications systems, designers often grapple with thedifficult problem of reliably transmitting a signal through a complexand dynamic environment. Fixed obstacles, such as buildings, streets orwalls reflect and refract transmitted signals in varying amounts,causing elements of the signals to be distorted, separated,phase-shifted or delayed. Dynamically moving obstacles, such asautomobiles, bicyclists, and pedestrians further complicate theenvironment, or transmission channel. Consequently, after beingtransmitted from a source location, multiple copies of the same signalmay be received at different times, at different phases, and withdiffering distortions at a single receiver, depending on the path eachrespective signal traversed through the transmission channel. Theseundesirable properties force designers to make various trade-offs amongsignal quality, propagation delay, channel capacity, amplification,frequency and error correction requirements.

In an effort to increase channel capacity, designers have implementedsystems which employ multiple antennas in both transmitters andreceivers. Typically, the antennas are spaced apart as an array at bothtransmission and reception locations. Each antenna within its respectivearray is generally configured to maintain a specific gain and phaserelationship with the other antennas within the array. These gain andphase relationships are typically maintained by weighting the signal,prior to transmission, with an appropriate weighting vector. In aproperly configured transmitter array, the end result is that the arrayproduces a transmission pattern that is more focused on a given receiverthan that which could be produced by a comparable single antenna.

Antenna arrays were previously used to improve signal quality. Use ofantenna arrays at both the transmitter and receiver has recently beenproposed to increase channel capacity. When multiple antennas are usedat the transmitter and receiver, the wireless channel between them maybe referred to as a multiple-input, multiple-output (MIMO) channel. MIMOsystems rely on the existence of multipath propagation between atransmitter and a receiver. Individual beams, pointing in differentdirections and carrying different traffic, can be fowled at amulti-antenna transmitter. In addition, individual received beams,carrying different traffic and arriving from sufficiently differentangles, can be separated at the multi-antenna receiver through acombination of nulling and subtraction.

To date, most MIMO systems have been constructed to minimize theprocessing power required at the mobile unit (which include, forexample, cellular telephones). Doing so allows the mobile units to besmaller, more power efficient and less expensive than they mightotherwise be. Consequently, system designers have typically kept theprocessor-intensive and power consuming mechanisms required to form andmanage individual data channels at the base station, where powersupplies are significantly greater and where the benefits of suchsystems outweigh their costs.

Base station only processing requires the base station to have ChannelState Information (CSI) describing the state of the communicationschannel between the base station and the mobile unit. In cellularsystems, for example, where the forward and reverse channels aretypically confined to different frequency bands, the CSI must beforwarded to the base station from the mobile units, which then requiressome increase in processing and power consumption at the mobile units.Techniques such as Minimum Mean Squared Error (MMSE), Transmit ZeroForcing, and the use of Filter Banks have been used to address theseproblems, but all have met with limited success.

Although MIMO systems frequently result in increased cost andcomplexity, MIMO systems have numerous advantages over their traditionalcounterparts. Perhaps most notably, MIMO systems are able todramatically increase the data throughput rate of a given channelwithout any associated increase in bandwidth or constellation order.This allows more information to be transmitted through the same channel,which facilitates clearer voice communications, higher data throughput,and more reliable wireless transmissions.

Despite their advantages, however, existing MIMO systems have also beenburdened with significant disadvantages. In a typical MIMO system, forexample, multiple signals are transmitted from multiple antennas at thesame time and at the same frequency. In these systems, the transmittedsignals will tend to interfere with each other, resulting in cross-talkamong wireless communication paths or channels. This interference isundesirable, and leads to signal distortion, phase shifting or evencancellation. Furthermore, in existing implementations, signal-to-noiseratios for individual data streams transmitted between a MIMOtransmitter and MIMO receiver may be substantially different, resultingin highly different bit error rates, and creating additionaldifficulties in transmission.

SUMMARY OF THE INVENTION

Thus, a need exists for an improved system and method for formingindividual channels between a transmitter and a receiver which cansupport multiple simultaneous signals, with significantly reduced oreliminated interference between the signals. A need also exists for animproved MIMO system which can transmit signals such that the individualdata streams have equal or near equal signal-to-noise ratios at the MIMOreceiver. Furthermore, a need exists for a reliable system which can beemployed in transmitters and receivers, mobile units and base stations.

In satisfaction of this need, systems and methods are provided foroptimizing the transmitter and receiver weights of a MIMO system. In oneembodiment, the weights within a MEMO transmitter and a MIMO receiverare optimized to create and steer beam nulls, such that each transmittedsignal is substantially decoupled from all other transmitted signals. Inanother embodiment, the weights are selected such that the signalstrength of each weighted signal transmitted through a communicationschannel along a respective signal path is substantially equivalent, butthe weighting vectors are not necessarily orthogonal, resulting inresidual crosstalk. In yet another embodiment, each transmitted signalis coupled only between its own transmitter and receiver antennas with again, or eigenvalue, that is a consequence of the weights, and which maybe bound to any desired range of values while at the same time, theweighting vectors remain orthogonal.

In accordance with one aspect of the invention, a MIMO signaltransmitter for use in a MIMO system is provided, wherein the MIMOsystem includes a receive array. The MIMO signal transmitter includes:two signal inputs, each signal input configured to provide a respectiveinput signal; two vector multipliers, each configured to weight arespective input signal with a vector to form a weighted signal; and,two antennas comprising a transmit array. The array is configured totransmit each weighted signal along a respective preferred signal path.Each vector is selected such that the signal strength of each weightedsignal received at the receive array along its respective signal path issubstantially equivalent.

In accordance with another aspect of the invention, a MIMO system isprovided. The MIMO system includes: a MIMO transmitter comprising afirst array of antennas, configured to transmit signals; a MIMO receivercomprising a second array of antennas configured to receive signals fromthe MIMO transmitter. A plurality of transmit vector multipliers are inelectrical communication with the MIMO transmitter, each configured toweight a respective transmit signal with a vector to form a weightedtransmit signal. A plurality of receive vector multipliers are inelectrical communication with the MIMO receiver. Each receive vectormultiplier is configured to weight a respective receive signal with avector to form a weighted receive signal. Preferably, each transmitvector is selected such that, at the MIMO receiver, the signal strengthof each weighted transmit signal received along a respective signal pathis substantially equivalent.

In accordance with yet another aspect of the invention, a method ofassigning antenna array weighting factors to a plurality of inputsignals for use in a MIMO system is provided. Preferably, the MIMOsystem includes a MIMO transmitter and a MIMO receiver. The methodincludes: in the MIMO transmitter, weighting each input signal with anappropriate transmit weight to form a plurality of weighted forward-linksignals; transmitting each of the weighted forward-link signals to aMIMO receiver; and in the MEMO receiver, choosing receive weights inorder to minimize the range of gain values, and to orthogonalize eachweighted forward-link signal received.

In accordance with yet another aspect of the invention, a method ofassigning antenna array weighting factors to a plurality of signals isprovided. In accordance with this method, a transmission matrixrepresenting a transmission channel through which the signal will travelis initially calculated. Next, a gain is calculated for each signal.Thereafter, the difference between the maximum and minimum values forthe calculated gains is determined. If the difference exceeds anacceptable level, the procedure is repeated by beginning at the initialstep and substituting a matrix component of the transmission matrix inthe subsequent first step. Thereafter, using the new matrix component toassign weighting factors to the plurality of signals.

In accordance with still another aspect of the invention, the inventionrelates to a multiple-input, multiple-output signal transmitter. Inaccordance with this aspect, the transmitter includes a plurality ofsignal inputs, each signal input configured to provide an input signal.The transmitter also includes a plurality of vector multipliers, eachvector multiplier is configured to weight an input signal with a vector(V). Furthermore, the transmitter includes a plurality of combiners,each configured to combine a plurality of weighted input signals. Thetransmitter also includes a plurality of antennas, each configured totransmit the combined weighted input signals.

Various embodiments of the transmitter aspects of the inventiondisclosed herein are possible. In one embodiment, V includes a matrix oftransmitter weighting coefficients, L includes a lower triangularmatrix, and the inverse of V is designated V¹ such that V⁻¹L⁻¹ includesa matrix of receiver weighting coefficients. In another embodiment, achannel matrix H is formed from the product of the lower triangularmatrix L and a unitary matrix Q, such that H=LQ. In an additionalembodiment, V includes a matrix of eigenvectors for the unitary matrixQ. In yet another embodiment, the at least two antennas include atransmit array, the transmit array configured to transmit each weightedsignal along a respective signal path; and wherein each vector V isselected such that the signal strength of each weighted signal receivedat a receive array along its respective signal path is substantiallyequivalent. In a further embodiment, the transmit array is furtherconfigured to receive transmitted signals from the receive array. Inanother transmitter embodiment, the matrix Q is decomposable such thatQ=V A V⁻¹. In another embodiment of the transmitter, A is a diagonalmatrix including at least one eigenvalue. In yet another embodiment, theat least one eigenvalue has a unit magnitude. In another transmitterembodiment, the matrix V is orthonormal.

In accordance with still another aspect of the invention, the inventionrelates to a multiple-input, multiple-output signal transmission system.In accordance with this aspect, the transmission system includes aplurality of signal inputs, each signal input configured to provide aninput signal and a plurality of transmit vector multipliers, eachtransmit vector multiplier configured to weight a respective inputsignal with a vector (V). The transmission system also includes aplurality of transmit combiners, each configured to combine a pluralityof weighted input signals; a plurality of transmit antennas, eachconfigured to transmit the combined weighted input signals; and aplurality of receive antennas, each configured to receive thetransmitted signals. Furthermore, the transmission system also includesa plurality of receive vector multipliers, each receive vectormultiplier configured to weight a respective transmitted signal with avector of the form V⁻¹L⁻¹; a plurality of receive combiners, eachconfigured to combine a plurality of weighted transmitted signals; and aplurality of signal outputs.

Various embodiments of the transmission system aspects of the inventiondisclosed herein are possible. In an one embodiment of the transmissionsystem, V includes a matrix of transmitter weighting coefficients, L isa lower triangular matrix and the inverse of V is designated such thatV⁻¹ L⁻¹ includes a matrix of receiver weighting coefficients. In anotherembodiment, H is a channel matrix formed from the product of the lowertriangular matrix L and a unitary matrix Q, such that H=L Q. In yetanother embodiment, V includes a matrix comprising eigenvectors for theunitary matrix Q. In a still further embodiment, the transmission systemfurther includes a plurality of digital to analog converters, eachconfigured to convert the weighted input signals from digital to analogprior to transmission by the transmit antennas. In another embodiment,the transmission system further includes a plurality of analog todigital converters, each configured to convert the weighted inputsignals form analog to digital upon reception by the receive antennas.In a further embodiment of the system, the matrix V is orthonormal.

In accordance with yet another aspect of the invention, a method ofassigning antenna array weighting factors to a signal for use in amultiple antenna transmitter is provided. The method includes steps ofcalculating a transmission matrix H representing a transmission channelthrough which the signal will be transmitted; using a firstdecomposition technique to decompose the transmission matrix II into aproduct of a lower triangular matrix L and a unitary matrix Q, such thatH=L Q; and orthogonalizing Q using a second decomposition technique todecompose the unitary matrix Q into a product of matrices. Thesematrices include a matrix V comprising transmitter weightingcoefficients; a diagonal matrix A comprising at least one eigenvalue;and an inverse matrix V⁻¹; such that Q=V A V⁻¹. The method furtherincludes the step of combining the results of the first decompositionand the second decomposition such that the transmission matrix H=L V AV⁻¹. In one embodiment of the method all eigenvalues have a unitmagnitude resulting in equal SNRs for the output signal. In anotherembodiment, matrix V is orthonormal providing equal power to eachparallel power amplifier.

Additional embodiments are also provided, as described within thespecification and attached claims.

In embodiments illustrating each of the foregoing aspects, the signal tonoise ratio for multiple signals traversing a transmission channel ispreferably optimized. In addition, the weights for each transmittedsignal are preferably selected so that the signals traversing atransmission channel each arrive at a respective receive antenna withapproximately the same signal strength.

BRIEF DESCRIPTION OF DRAWINGS

These and other aspects of this invention will be readily apparent fromthe detailed description below and the appended drawings, which aremeant to illustrate and not to limit the invention, and in which:

FIG. 1 depicts a high-level schematic diagram of a communicationschannel illustrating the various signal transformations comprising aMIMO system.

FIG. 2 illustrates an embodiment of a two-input, two-output MIMO system.

FIG. 3 depicts an expanded block diagram illustrating preferred elementswithin a transmitter and a receiver.

FIG. 4 depicts a 2×2 MIMO system comprising a MIMO transmitter and aMIMO receiver, in accordance with one embodiment of the presentinvention.

FIG. 5 is a flow chart representing a weighting method for a MIMOsystem, in accordance with another embodiment of the present invention.

FIG. 6 shows a block diagram illustrating certain signal processingfunctions incorporated into yet another embodiment of the claimedinvention.

In the drawings, like reference characters generally refer tocorresponding parts throughout the differing views.

DETAILED DESCRIPTION OF THE INVENTION

In brief overview, embodiments of the present invention provide systemsand methods for increasing the effectiveness of MIMO transmission andreception by selecting signal weights for a plurality of signals whichprovide equivalent signal strength for each transmitted signal at eachreceive antenna within a MIMO array.

In addition, embodiments of the present invention provide systems andmethods for increasing the effectiveness of MIMO transmission byselecting signal weights for a plurality of signals which provide equal,composite signals strengths to each power amplifier in the MIMOtransmitter, thereby assuring equal power back-off from saturation andhence enabling higher power-added efficiency.

FIG. 1 depicts a high-level schematic diagram of a communicationschannel, generally designated as 100, illustrating the various signaltransformations utilized in a MIMO system. In the preferred embodiment,an input signal S_(IN) 102 represents information that will betransmitted by a MIMO transmitter, through the communications channel100, and eventually received by a MIMO receiver and decoded to producean output signal 114. The input signal 102 is a complex vector with onecomplex entry for each transmit antenna. Preferably, the input signal102 is weighted by a weighting matrix 104 in order to produce anadaptive array antenna signal z(k) for each time sample k. This signalz(k) is also preferably a complex vector with one complex entry for eachtransmit antenna. The weighted signal is then upconverted andtransmitted wirelessly through a transmission channel 106, which isrepresented mathematically by a time-varying channel matrix H(k).

The channel matrix 106 represents the transmission channel between thetransmit array and the receive array in the MIMO system. As before, thechannel matrix 106 is a time varying matrix with one complex entry foreach transmission channel at each time sample k. Thermal noise anddynamic environmental variations 108 are preferably representedmathematically by a noise vector n(k). Noise vector n(k) is alsopreferably a complex vector with one complex entry for each transmissionchannel at each time sample k. The combination of the environmentalvariations 108 and the signal 102 occurs in a summation element 110,represented mathematically as a Σ. The final received signal ismathematically represented by receive vector r(k), again a complexvector quantity. The signal 102 is then preferably weighted by a receivematrix 112, with one complex entry for each receive antenna and multiplesignal combination at each time sample k, mathematically represented asU(k), to produce the output signal 114.

Note that in a noise free communications channel 100, all data streamscan be recovered perfectly if the channel matrix 106 is full rank. Forexample, in a system comprising two transmission antennas, two receiveantennas and two transmitted signals, two equations and two unknowns canbe solved within the channel matrix 106.

FIG. 2 illustrates one embodiment of a two-input, two-output MIMOsystem. As shown, a transmitter 202 includes at least two antennas A, B.A receiver 204 also includes at least two antennas C, D. Between thetransmitter 202 and the receiver 204 are a first wall 206, a second wall208 and possibly, an obstacle 210.

In this embodiment, the transmitter 202 transmits multiple signals fromeach of its antennas A, B, to the antennas C, D of the receiver 204.However, the individual signals may travel along very different pathsbetween the transmitter 202 and receiver 204. For example, a firstsignal, 205 may be broadcast in a first direction from transmit antennasA and B, then reflected off the first wall 206 and arrive at antennas Cand D of the receiver 204 from the first direction. At the same time, asecond signal 207 may leave transmit antennas A and B in a seconddirection, reflect off the first wall 206, pass through an obstacle 210,and reflect off the second wall 208 before finally arriving at antennasC and D of the receiver 204 from the second direction.

Preferably, the transmitter 202 transmits signals from each antenna A, Bsimultaneously. As these signals preferably originate from a single datastream or set of data streams, they may be similar in frequency,magnitude and content. In traditional MIMO systems, these two signalswould likely interfere with each other. However, embodiments of theclaimed invention minimize or entirely eliminate this unwantedinterference.

FIG. 3 depicts an expanded block diagram illustrating preferred elementswithin the transmitter 202 and the receiver 204. In this embodiment, thetransmitter 202 includes a signal input 312, a demultiplexor 302, twotransmission processors 304, 306, two summation elements, or combiners308, 310 and two transmit antennas A, B. The input of the demultiplexor302 is electrically connected to the signal input 312. The demultiplexor302 preferably includes at least two outputs, each of which areelectrically connected to the inputs of a respective transmissionprocessor 304, 306. Each transmission processor 304, 306 preferablyincludes at least two outputs, with each output electrically connectedto an input of a respective combiner 308, 310. In the illustratedembodiment, the output of a first combiner 308 is electrically connectedto transmit antenna A. Similarly, the output of a second combiner 310 iselectrically connected to transmit antenna B.

In this embodiment, the receiver 204 includes two receive antennas C, D,two receive processors 314, 316, a multiplexor 318, and a signal output320. Preferably, the receive antennas C, D are cross-connected with theinputs of the receive processors 314, 316. Accordingly, antenna C iselectrically connected to an input of a first receive processor 314 andan input of a second receive processor 316. Similarly, antenna D iselectrically connected to another input of the first receive processor314 and another input of the second receive processor 316. The outputsof the receive processors 314, 316 are then preferably coupled to theinput of the multiplexor 318. Thereafter, the output for the multiplexor318 includes the signal output 320 of the receiver 204.

In operation, a signal enters the transmitter 202 through the signalinput 312. The demultiplexor 302 splits the signal into two or morecomponents, and provides these signal components to the transmissionprocessors 304, 306. Preferably, the transmission processors 304, 306then weight each signal component with a specified weighting vector. Asspecified previously, this weighting vector preferably includes onecomplex entry for each transmitter antenna. The weighted signalcomponents are then communicated to the combiners 308, 310, whichcombine the respective weighted signal components. Thereafter, the twoweighted signals are preferably upconverted and transmitted as radiofrequency signals through the transmit antennas A, B.

After travelling through the transmission channel (See FIG. 1) thesignals are preferably received by two antennas C, D connected to thereceiver 204. The antennas C, D then preferably supply the weightedsignals to each of the two receive processors 314, 316. In thisembodiment, the receive processors 314, 316 multiply each of thereceived signals by a respective weighting vector. Thereafter, thesignals are transmitted to the multiplexor 318, which combines thesignals and outputs them through signal output 320.

FIG. 4 depicts a 2×2 MIMO system 400 comprising a MIMO transmitter 402and a MIMO receiver 404. The transmitter 402 includes a first signalinput 406, a second signal input 408, two optional water-fillingmultipliers 410, 412, four transmit multipliers 414-417, two combiners418, 420 and two transmit antennas A, B. Each water-filling multiplier410, 412 is configured to multiply a signal by a correspondingwater-filling weight α₁, α₂. Similarly, each transmit multiplier 414,415, 416, 417 is configured to multiply a signal by a correspondingtransmit vector V₁₁, V₂₁ and V₁₂, V₂₂. In this embodiment, the input tothe first optional water-filling multiplier 410 is preferably connectedto the first signal input 406, and its output is electrically connectedto the respective inputs for a first transmit multiplier 414, and asecond transmit multiplier 415. The output of the first transmitmultiplier 414 is electrically connected to a first combiner 418. Theoutput of the second transmit multiplier 415 is electrically connectedto a second combiner 420. Similarly, the input to the second optionalwater-filling multiplier 412 is preferably connected to the secondsignal input 408, and its output is electrically connected to therespective inputs for a third transmit multiplier 416 and a fourthtransmit multiplier 417. The output of the third transmit multiplier 416is electrically connected to the first combiner 418. The output of thefourth transmit multiplier 415 is electrically connected to the secondcombiner 420. The first combiner's 418 output is preferably transmittedthrough antenna A, while the second combiner's 420 output is preferablytransmitted through antenna B.

In a conventional MIMO system, water-filling multipliers are chosen sothat the individual signal levels at the receiver are equal, henceyielding equal signal-to-noise ratios and packet error rates. However,in doing so, the composite signal strengths provided to the multiplepower amplifiers of the MIMO transmitter may be substantially different,resulting in different power back-off, and hence reduced power-addedefficiency for the power amplifiers.

Unlike a conventional MIMO system, the water-filling multipliers 410,412 and their corresponding weights α₁, α₂ depicted in FIG. 4 areoptional and not necessary in this embodiment. This embodiment, however,still maintains equal or near equal signal levels at the MIMO receiver404 and equal or near equal composite signal levels at the inputs to themultiple power amplifiers of the MIMO transmitter 402. Further, thisembodiment maximizes the equal signal levels at the MIMO receiver 404,thereby maximizing the signal-to-noise ratios of the received signals.Accordingly, these water-filling multipliers 410, 412 and thecorresponding weights α₁, α₂ may be absent or varied in alternateembodiments.

The receiver 404 includes four receiver multipliers 422-425, a thirdcombiner 426, a fourth combiner 428, a first signal output 430 and asecond signal output 432. Antennas C and D are configured to receivesignals transmitted from the transmitter 402. In this embodiment,antenna C is electrically connected to the inputs of a first receivermultiplier 422 and a second receiver multiplier 423. The output of thefirst receiver multiplier 422 is preferably electrically connected tothe input of the third combiner 426. The output of the second receivermultiplier 423 is preferably electrically connected to the input of thefourth combiner 428. In a similar fashion, antenna D is electricallyconnected to the inputs of a third receiver multiplier 424 and a fourthreceiver multiplier 425. Preferably, the output of the third receivermultiplier 424 is electrically connected to an input of the thirdcombiner 426. In addition, the output of the fourth receiver multiplier425 is preferably electrically connected to an input of the fourthcombiner 428. Finally, the output of the third combiner 426 istransmitted to the first signal output 430, while the output of thefourth combiner 428 is transmitted to the second signal output 432. Inthis embodiment, each receiver multiplier 422, 423, 424, 425 isconfigured to multiply the signals received by a corresponding receivevector U₁₁, U₂₁ and U₁₂, U₂₂.

Mathematical Description.

The following mathematical description describes the computationalprocessing comprising various embodiments of claimed invention withreference to FIGS. 1-4.

In general, any wireless communications link having multiple antennaslocated at both a transmitting end and at a receiving end can berepresented by a transmission matrix H, the elements of which representthe individual transfer functions between all pairs of transmit andreceive antennas. In order to make full use of the channel capacityoffered by such a link, it is necessary to provide weights at both thetransmitter and receiver, such that a resulting cascaded matrix becomesdiagonal. Multiple, independent signals can then be transmittedsimultaneously from the transmitter to the receiver, as depicted invarious embodiments of the claimed invention. One such embodiment isdepicted in FIG. 4, which illustrates a 2×2 MIMO system having twotransmitter antennas and two receiver antennas. Also shown are theassociated processing weights, V_(Jk) and U_(jk) for MIMO operation, andoptional water-filling weights, a_(j) as necessary.

If multiple input signals are represented by vector s_(i) and themultiple output signals are represented by the vector s_(o), then:s _(o) =U ^(T) HVs _(i)

Where U represents the vector of weights at the receiver, V representsthe vector of weights at the transmitter and U^(T) represents thetranspose of the vector U. If U and V are chosen correctly, then:U ^(T) HV=A

where Λ is a diagonal matrix.

As a result, the multiple output signals become representations of themultiple input signals each multiplied by a different value of theprincipal diagonal of the matrix Λ.s _(o) =Λs _(i)

For any matrix H, eigenvectors x_(i) exist that satisfy therelationship:Hx _(i) =λ,x _(i)

where λ, is a complex constant called an eigenvalue. The multipleeigenvector solutions to the above equation can be grouped together ascolumn vectors, in a matrix X. This allows the multiple eigenvectorequations to be written as a matrix equation:HX=XΛ

where the individual eigenvalues form the diagonal elements of thediagonal matrix Λ.

Matrix Forms.

A Unitary matrix is one whose transposed element values are equal to thecomplex conjugate of the elements of its inverse:H ^(T) =H ⁻¹*

A result of the above property is that the individual column (or row)vectors h_(j) that make up a unitary matrix are mutually perpendicular(orthogonal for a matrix of real values).h _(j)*^(T) h _(k)=1, where j=khj* ^(T) hk=0, where j≠k

In addition, the eigenvalues of a Unitary matrix all lay on the unitcircle of the complex plane.

A Hemtitian matrix is one whose transposed element values are equal tothe complex conjugate of its elements:H _(T) =H*

Where the superscript (^(H)) denotes conjugate transpose, the followingidentity applies:H=H* ^(T) =H ^(H)

A property of a Hermitian matrix is that a matrix composed of itseigenvectors is Unitary, In addition, the eigenvalues of a Hermitianmatrix all lay on the positive real axis of the complex plane.

Eigenvalue Decomposition (EVD).

As set forth below, the Eigenvalues of a channel matrix provide a methodfor diagonalization, and hence for a projected increase in channelcapacity with MIMO. For example, in operation of the 2×2 embodimentdepicted in FIG. 4, two statistically independent signals, S_(i in) arepreferably input to the transmitter 402 through the signal inputs 406,408. The signals are optionally multiplied 410, 412 by water-fillingweights α₁. and subsequently multiplied 414-417 by the transmitterweights and combined with the associated power combiners 418, 420.

At the transmitter 402, the Eigenvalue Decomposition (EVD) transmitterweights, V_(ij) form column vectors, V₁ that establish the individualtraffic channels. The water-filling weights, oc_(i) can be used to helpincrease channel capacity by allowing the signal levels at the receiverto be equal. However, this will also cause the composite signal levelsdelivered to the multiple power amplifiers to be different, producingdifferent power back-off and lower power-added efficiency.

The multiple eigenvector equations can be written as the matrixequation:HX=XΛ

where H represents the link transmission matrix and A represents adiagonal matrix, the elements of which include the individualeigenvalues. Post-multiplying both sides of the above equation by X⁻¹yields:H=XΛX ⁻¹

In operation, first consider Eigenvalue Decomposition withoutwater-filling. If the receiver weights U^(T) are chosen to be theinverse of X, and if the transmitter weights V are chose to be equal toX, then:

$\begin{matrix}{s_{0} = {U^{T}{HVs}_{i}}} \\{{= {X^{- 1}{HXs}}};} \\{= {X^{- 1}{XAX}^{- 1}{Xs}_{i}}}\end{matrix}$

And:s _(o) =Λs _(i)

One difficulty with Eigenvalue Decomposition is that there is nocertainty that the channel matrix will be full rank, thereby ensuring asufficient number of eigenvectors. A second difficulty with EigenvalueDecomposition is that the eigenvectors are not mutually perpendicular,since the weighting matrices formed from the eigenvectors are notUnitary. This can result in cross-talk between the multiple signals onthe link.

A third difficulty with Eignevalue Decomposition is that the eigenvaluesmay vary greatly in magnitude. Large variations in magnitude result inbetter signal-to-noise ratios for some of the signal channels s_(o), atthe expense of the signal-to-noise ratios for some others. To someextent this can be compensated for using water filling techniques,described below.

The channel capacity for a Gaussian channel is given by:Ci=log₂(1+Pi)

where P_(i) represents the channel signal to noise ratio, SNR_(i), atthe receiver. Water-filling is a method that increases the totalcapacity for a multiple channel link, by filling each channel to acommon level, D:1/λ1+P ₁=1/λ₂ +P ₂ ==D

where the eigenvalues, λ_(i) represent the gains for the channels. Forindependently corrupted channels, the total signal to noise ratio at thereceiver is the summation of the signal to noise ratios for theindividual channels, P_(i):P=ΣP _(i)

The water-filling coefficients are then given by:α₁ =P _(i) /P

As a result, the channel with the highest gain (largest eigenvalue) willreceive the largest share of the power.

A fourth difficulty with Eigenvalue Decomposition is that the compositesignal levels delivered to the multiple power amplifiers will mostlikely be different, producing different power back-off and lowerpower-added efficiency.

Singular Value Decomposition (SVD).

Again, consider the 2×2 embodiment depicted in FIG. 4. In thisembodiment, two statistically independent signals, S, ;₁, are preferablyinput to the transmitter 402 through the signal inputs 406, 408. Thesignals are optionally weighted by water-filling weights 410, 412 a, andsubsequently weighted by the transmit weights 414-417 V_(ij) andcombined with the associated power combiners 418, 420.

Here, the SVD weights, V_(ij) form column vectors, V_(i) that help toestablish the individual traffic channels, and the optionalwater-filling weights, α_(i), help to increase the channel capacity.

Similarly, the signals arriving from the receive antennas C, D, passthrough the SVD receive weights U_(ij) 422-425. Again, these weightsform column vectors, U_(i); that help to establish the individualtraffic channels.

The transmission matrix, H representing individual paths from thevarious transmitter antennas to the various receiver antennas, includesvarious elements H_(ij).

For any matrix, H, the Gramm matrix H^(H)H and the outer product matrixH H^(H) are both Hermitian. As before, the ^(H) superscript denotes aconjugate transpose operation.

Further, the Eigenvalues, λ_(i) have the same values for both H^(H)H andH H^(H). Hence:(H ^(H) H)V=VΛand:(HH ^(H))U=UΛ

where A is the diagonal matrix of λ_(i) is the unitary matrix [U₁, U₂ .. . U_(n)] of eigenvectors of G=H H^(H) and V is the unitary matrix [V₁,V₂ . . . V_(n)] of eigenvectors of H^(H)H. In order to satisfy both ofthe above eigenvector equalities (for the Gramm matrix and for the outerproduct matrix), the channel transfer matrix can be written as:H=UΛ ^(1/2) V ^(H)

In operation, first consider Singular Value Decomposition withoutwater-filling. Here, the input signals, S, pass through the transmitterSVD weights, V_(ii) and are radiated through the transmission matrix, Hto the receive antennas. Mathematically, this can be represented by H V.From the above equation, this can also be represented by:

$\begin{matrix}{H = {U\;\Lambda^{1/2}V^{H}V}} \\{= {U\;{{\Lambda 1}/2}}}\end{matrix}$

Upon reception, the signals pass through the receiver SVD weights,U_(ij) to form the output signals, S_(i out). Using the above equation,this can be represented by:

$\begin{matrix}{s_{0} = {U^{H}{HVs}_{i}}} \\{{= {U^{H}U\;\Lambda^{1/2}s_{i}}};} \\{= {\Lambda^{1/2}s_{i}}}\end{matrix}$

Writing this explicitly for each individual output signal, Si outyields:Si _(out)=λ_(i) ^(1/2) S _(i in).

One advantage of Singular Value Decomposition is that full rank of thedecomposition process is guaranteed, thereby ensuring the requirednumber of singular values (the square root of the eigenvalues of theGramm matrix).

A second advantage of Singular Value Decomposition is that theeigenvectors are all mutually perpendicular, since the weightingmatrices formed from the eigenvectors are Unitary. This can result insignificant suppression of cross-talk between the multiple signals onthe link.

A third advantage of Singular Value Decomposition is that, since thematrix folliied by the transmitter complex weights is unitary, thecomposite signal strengths delivered to the multiple power amplifiers ofthe MIMO transmitter will by equal.

One disadvantage with Singular Value Decomposition is that, while theeigenvalues are real, they may vary greatly in magnitude. Largevariations in magnitude result in better signal-to-noise ratios for somesignal channels s_(o), at the expense of the signal-to-noise ratios forothers. Water-filling techniques can compensate for this disadvantage,to a certain extent, but will cause unequal contributions to thecomposite signal strengths being delivered to the transmitter poweramplifiers. This will result in an overall decrease in signal levelsdelivered to the receiver with real, power limited power amplifiers.

Once the transmission matrix, H of the channel has been determined, theHelluitian matrix, G can be found. Let H be given as:

$H = \begin{bmatrix}H_{11} & H_{12} \\H_{21} & H_{22}\end{bmatrix}$

Then:

$\begin{matrix}{G = \begin{pmatrix}{{H_{11}}^{2} +} & {H_{12}}^{2} & {{H_{11}^{*}H_{21}} +} & {H_{12}^{*}H_{22}} \\{{H_{11}H_{21}^{*}} +} & {H_{12}H_{22}^{*}} & {{H_{22}}^{2} +} & {H_{21}}^{2}\end{pmatrix}} \\{= \begin{pmatrix}a & c \\c^{*} & b\end{pmatrix}}\end{matrix}$

And:

$\lambda_{\max} = {{1/2}\left( {a + b + \sqrt{\left( {a - b} \right)^{2} + {4{c}^{2}}}} \right)}$$\lambda_{\min} = {{1/2}\left( {a + b - \sqrt{\left( {a - b} \right)^{2} + {4{c}^{2}}}} \right)}$

Unit Magnitude Decomposition (UMD).

An arbitrary channel matrix H can be written as the product of a unitarymatrix Q and an upper triangular matrix R.H=QRor:HR ⁻¹ =Q

Here, Q and R⁻¹ can be found using the Gram-Schmidt procedure (or usingthe Householder or Givens transformations).

Now, the unitary matrix can be expressed in terms of its eigenvectorsand eigenvalues as:QV=VΛor:Q=VΛV ⁻¹

where the eigenvalues of Λ lay on the unit circle. Combining the twoexpressions yields:HR ⁻¹ =VΛV ⁻¹or:H=VΛ(V ⁻¹ R)

If the weights on the transmitter are set equal to (R⁻¹ V), then thesignals at the receiver antennas become:H(R ⁻¹ V)=VΛ

In addition, if the weights on the receiver are set equal to V⁻¹, thematrix relating the input signals s_(i) to the output signals s_(o)becomes:V ⁻¹ H(R ⁻¹ V)=Λand:s _(o) =Λs _(i)

Unit Magnitude Decomposition thus decomposes an arbitrary channel matrixinto the product of a Unitary matrix and an Upper triangular matrix.Since the eigenvalues for a unitary matrix all lay on the unit circle,the signal-to-noise ratios for each of the signals s_(o) will be equal,thereby minimizing packet error rate degradation due to unequalsignal-to-noise ratios. However, in this procedure there is no guaranteethat the decomposition will be full rank, resulting in the requirednumber of eigenvalues. Further, there is no guarantee that theeigenvectors will be orthogonal, or that the composite signal levelsdelivered to the transmitter power amplifiers will be equal.

Accordingly, the weights of both a transmitter and a receiver can bedetermined by employing the mathematical operators described above.

Alternative Unit Magnitude Decomposition (AUMD)

The Unit Magnitude Decomposition (UMD) technique discussed aboverepresents one technique for decomposing a system channel matrix H. Thistechnique is advantageous in some applications because it yields equalsignal-to-noise ratios at the outputs of the receiver, for the multipledata streams in a MIMO system or device. However, in some embodiments ofthe UMD technique, equal signal levels at the transmitter poweramplifiers are not achieved. This can occur when the transmitterweighting coefficient matrix R⁻¹ V is not orthonormal. Accordingly, insome instances, a reduction in the range of the wireless link as well asthe power efficiency of the transmitter can occur. In light of thesepossible constraints, in some instances, it is desirable to consider theAlternative Unit Decomposition (AUMD) technique for use with varioussystem, method and device embodiments of the invention.

According to one embodiment of the AUMD technique, an arbitrary channelmatrix H can be written as the product of a lower triangular matrix Land a unitary matrix Q.H=LQThe AUMD technique is based upon a decomposition of the L Q productfollowed by an eigenvalue decomposition on Q. In contrast, the UMDapproach uses a Q R decomposition followed by an eigenvaluedecomposition on Q.

Once the channel matrix H has been determined, the unitary matrix Q canthen be orthogonalized using eigenvalue decomposition. As a result, theunitary matrix Q can be expressed in terms of its eigenvectors andeigenvalues as:Q=VΛV ⁻¹

Similarly, a direct substitution for Q allows the channel matrix to beexpressed as:H=LVΛV ⁻¹

If the transmitter weighting coefficients are chosen to be V, and thereceiver weighting coefficients are chosen to be V⁻¹ L⁻¹, then theoutput signals So will be related to the input signals S_(i) by:

$\begin{matrix}{S_{0} = {\left( {V^{- 1}L^{- 1}} \right){H(V)}S_{i}}} \\{= {\left( {V^{- 1}L^{- 1}} \right)\left( {{LV}\;\Lambda\; V^{- 1}} \right)(V)S_{i}}}\end{matrix}$

And thus:S _(o) =ΛS _(I)

The AUMD also enables MIMO operation with equal signal-to-noise ratiosat the receiver outputs. Again, this is a result of the eigenvalues in Λall having unit magnitudes. In addition, the AUMD technique providesequal signal levels at the transmitter power amplifiers, since thetransmitter weighting coefficient matrix V is now orthonormal.Accordingly, the weighting coefficients of both a transmitter and areceiver can be determined by employing the mathematical operatorsdescribed above while obtaining the benefits associated with equalsignal levels.

Successive Decomposition with a Final SVD.

In alternate embodiments, a Successive Decomposition with a Final SVDprocedure may initially make use of Singular Value Decomposition toensure orthogonal complex weighting vectors (orthogonal eigenvectors)for each signal. If the resulting gains or eigenvectors for each signalvary greatly in magnitude, then instead of using SVD, the channel matrixis decomposed using a known decomposition procedure into a new matrix, Rpre-multiplied by a unitary matrix and post-multiplied by the adjointmatrix of the unitary matrix. Decomposition procedures that achieve theabove include the Schur decomposition as well as the Hessenbergdecomposition.

The Schur decomposition converts a complex square matrix, H into theproduct of a unitary matrix Q, an upper triangular matrix, R, and theadjoint matrix of the unitary matrix, Q*.

Like the Schur Decomposition, the Hessenberg Decomposition converts acomplex square matrix, H into the product of a unitary matrix, Q, aHessenberg matrix, A, and the adjoint matrix of the unitary matrix, Q*.The Hessenberg matrix has zero for the values of all elements below thediagonal immediately below the principal diagonal.

The new matrix is then further decomposed using SVD, and since theorthogonal eigenvectors of SVD cascade with the first pre-multipliedunitary matrix and the second post-multiplied unitary matrix, thecomplex weighting vectors for each signal remain orthogonal. If thegains (singular values) of the SVD of the new matrix are within anacceptable range, then the procedure is completed. However if the gainsvary greatly in magnitude, the process is repeated with one of the knowndecomposition procedures being applied to the new matrix, R. Theprocedure is repeated until the eigenvalue gains are within anacceptable range. One skilled in the art will readily recognize that theacceptable range would vary with each specific embodiment, but mayinclude, without limitation, gain variances between about 150% and 300%.Mathematically, this technique can be illustrated as set forth below.

After performing a Singular Value Decomposition, the channel matrix Hcan be represented as:H=U ₀Λ₀ ^(1/2) V ₀

If decomposition of the channel matrix H results in singular values thatvary greatly in magnitude, then the channel matrix can be alternativelydecomposed using a Schur Decomposition procedure or a Hessenbergprocedure. This decomposition converts a complex square matrix, H intothe product of a unitary matrix Q₁, a new matrix R₁, and the adjointmatrix of the unitary matrix Q^(*) ₁. Thus, for the Schur or HessenbergDecomposition, we have:H=Q ₁ R ₁ Q* ₁

The new matrix, R₁, can then be decomposed using SVD to achieve a newdiagonal matrix (of singular values), Λ₁ ^(1/2) pre-multiplied by aunitary matrix U₁ and post-multiplied by another unitary matrix V₁.R ₁ =U ₁Λ₁ ^(1/2) V ₁

Combining the Schur (or Hessenberg) Decomposition and the Singular ValueDecompositions yields:H=Q ₁ U ₁Λ₁ ^(1/2) V ₁ Q ₁

Since the multiplication of two unitary matrices results in a newunitary matrix, we have:H=U ₂Λ₁ ^(1/2) V ₂

This is a new decomposition having unitary matrices (composed oforthogonal eigenvectors) and a diagonal matrix with new singular values.If the singular values have magnitudes that are within an acceptablerange, the Successive Decomposition with a Final SVD is finished.However, if the singular values vary greatly in magnitude, the processis repeated with the Schur (or Hessenberg) Decomposition being appliedto the new matrix R₁.H=QAQ*

The procedure can, in fact, use both the Schur and HessenbergDecomposition at each iterative stage, and select the Decompositionwhich produces eigenvalue gains that are most tightly bound. Othermatrix Decomposition operations that result in a new matrixpre-multiplied and post-multiplied by unitary matrices can also be usedin the Successive Decomposition with a Final SVD procedure.

The SVD procedure provides full rank (ensuring the necessary number ofeigenvalues), orthogonal eigenvectors (minimizing signal cross-talk),equal composite power levels to the multiple power amplifiers(minimizing back-off from saturation), and, with water-filling, equalpower levels at the receiver. The water-filling, however, actuallydecreases the (equal) power levels at the receiver to levels below whatis achievable. Thus, Successive Decomposition With a Final SVD ensuresfull rank, orthogonal eigenvectors, equal composite power levels to themultiple power amplifiers, and near equal power levels at the receiverat the maximum level achievable (since water-filling is not used). Sincethe cascaded unitary matrices reduce to another unitary matrix, theeigenvectors will be orthogonal, and the composite signal strengthdelivered to the transmitter power amplifiers will be equal. Finally,the eigenvalues will be bounded within an acceptable range.

In alternate embodiments, the channel matrix values can be measured apriori using known techniques and the appropriate decomposition can becalculated. Thereafter, the weights may be transmitted from thetransmitter to the receiver or from the receiver to the transmitter.

FIG. 5 is a flow chart representing a weighting method for a MIMOsystem, in accordance with another embodiment of the present invention.As illustrated in this embodiment, an elegant and rapid iterativeoptimization can be used to obtain the transmission and receiveweighting values through an unspecified decomposition. Preferably, thewireless communications channel in this embodiment includes a TimeDivision Duplex (TDD) channel, however other channels are alsoappropriate.

In this embodiment, the transmitter weights at one end of the link, V,are arbitrarily set equal at initialization (step 500). Through theforward link, the transmitter broadcasts signals through a plurality ofchannels to the receiver using the transmitter weights V, (step 502).The receiver then receives the signals broadcast from the transmitter(step 504). Upon reception of the signals at the receiver, the receiveweights U, are chosen to maximize each channel's individual gain (step506). These chosen receive weights, U, are then preferably used fortransmission on the reverse link, since the wireless LAN channel isreciprocal (step 508). Upon reception, the transmit weights V, arepreferably chosen to maximize each channel's individual gain (step 510)for the reverse link. In this embodiment, the decomposition finallyachieved is not predictable.

After the transmitter has adjusted its weights accordingly, the systemin this embodiment determines whether or not there is more informationavailable for transmission (step 512). If not, the method ends (step514). If there is more information to be transmitted, the systempreferably determines whether or not the weights are optimal (step 516).Preferably, the iterative adjustment of the weights on the forward andreverse links will converge to the Unitary system of vectors V, andAccordingly, if the transmitter determines that its weights V_(i) haveconverged to a Unitary matrix, then condition for step 516 could bedeemed true. One skilled in the art will also recognize that many othermethods and processes may also be used to determine whether or not theweights V, and U₁ are optimal, in accordance with step 516. For example,in alternate embodiments, the determination of whether or not theweights are optimal may include, without limitation, determining:

(a) whether the weights V, and LI, are selected such that the signalstrength of each weighted signal received at a receive array along itsrespective signal path is substantially equivalent;

(b) whether the eigenvalues of a channel matrix between the receiver andthe transmitter have equal magnitudes;

(c) whether the eigenvalues of the channel matrix lie substantially onthe unit circle of the complex plane;

(d) whether the nulls of the array and the nulls of the transmitter andthe receiver have been configured such that the signal strength of eachweighted signal received at the receiver along its respective signalpath is substantially equivalent; or

(e) a combination of any of the foregoing.

If the weights V, and U, are deemed optimal in step 516, then the systemtransmits additional signals using the existing weights (step 518).Otherwise, the system returns to step 502, and repeats the iterativeprocess, further refining the weights through each successive iteration.

FIG. 6 shows a block diagram illustrating certain signal processingfunctions incorporated into one embodiment of the claimed invention.This embodiment includes a transmitter 600 and a receiver 602, which arepreferably capable of broadcasting and receiving signals according tothe IEEE 802.11a standard. In alternate embodiments, the transmitter 600and receiver 602 may be configured to transmit and receive signalsdefined by other specifications, including, without limitation, IEEE802.11b, 802.11g, or any radio frequency signal, including, withoutlimitation, IS95. Preferably, this embodiment provides a two-times datarate enhancement. The MIMO functions, as described previously, arepreferably accomplished through the use of the demultiplexor 604 anddecomposition block 606 in the transmitter and the multiplexor 608 andrecomposition block 610 in the receiver.

In operation, the demultiplexor 602 preferably separates a high datarate input signal (for example, approximately 108 Mbps) into twoparallel lower rate signals (for example, 54 Mbps), each traversing astandard set of communications operations. The two OFDM modulatedsub-carriers are output, in the time domain, from the two antennas A, B.In the receiver 602, the recomposition block 610 preferably separatesthe blended signals back into their two original, individual datastreams. These data streams then undergo further standard operationsbefore being recombined by the multiplexor 608 to form the original highdata rate signal.

In this embodiment, the decomposition operation is shown to take placeon all sub-carriers together for an OFDM signal. One skilled in the artwill readily appreciate that in situations having a high degree offrequency selective fading, the decomposition operation can also beperformed on smaller groups of sub-carriers, or on each sub-carrierindividually.

In alternative embodiments, the two parallel chains of computationaloperations in both the transmitter 600 and receiver 602, as shown inFIG. 6, could also potentially be replaced with a single chainperforming the operations of the two chains sequentially in time atdouble the clock rate. This topology has the advantage of smaller sizeand construction cost at the expense of consuming higher power per gate,based upon the increased clock rate.

In a MIMO environment, in order to realize the potential increase indata throughput rate, the received signals should preferably have a highsignal to noise plus interference ratio (SNIR). Accordingly, a SNIR onthe order of about 25 dB is preferable. This ratio is markedly higherthan a non-MIMO communications link, which typically mandates a SNIR ofonly about 10 dB. This required SNIR ratio also implies a requirementfor very low, externally generated, co-channel interference.

Even when a high SNIR is attained, MIMO operation frequently requires avery high degree of linearity in the front-end analog and RF circuits ofthe transceiver in order to achieve the maximum potential increase indata throughput rate. Furthermore, group-delay dispersion and diffuseangle-of-arrival can also severely restrict the potential increase indata throughput rate.

These non-ideal front-end circuit and non-ideal channel limitations canbe more easily addressed by eliminating the sources of the problems atthe receiver input, rather than by canceling the impairments with signalprocessing in the backend. Techniques such as adaptive predistortion ofthe transmitter power amplifiers can be used.

There are many advantages that embodiments of the present inventionenjoy over the prior art. For example, embodiments employing UnitMagnitude Decomposition to obtain weighting coefficients used in thetransmitter and the receiver effectively locate the eigenvalues of therespective weighting matrices on the unit circle of the complex plane,resulting in all signals enjoying the same signal-to-noise ratio,independent of environment. In other embodiments employing theSuccessive Decomposition with a Final SVD techniques, the weightingvectors are orthogonal, thereby minimizing crosstalk and ensuring equalcomposite power levels to the multiple power amplifiers, while at thesame time the eigenvalues are bound within an arbitrarily small range,thereby equalizing individual channels' signal-to-noise ratios.

Advantageously, embodiments of the present invention also make use ofprocessing available at both the transmitter and receiver. Thisprocessing not only provides increased data throughput, but also fullorder diversity against fading signal levels. Furthermore, processing atboth the transmitter and receiver, as specified herein, is particularlyadvantageous when the forward and reverse channels are identical, as inTime Division Duplexing links. Not only do the transmitters at both endsof the link have knowledge of the same channel, their individual weightscan be used for both transmission and reception.

In addition to being attractive for TDD channels, processing at both thetransmitter and receiver is attractive where reasonable processing powerexists at both channel ends. It is also attractive where reasonableantenna separation is available at both ends of the link. Accordingly,embodiments of the present invention make use of the processing powerprovided by modern electronic devices, such as laptop computers, inorder to increase wireless data throughput.

It will be appreciated, by those skilled in the art, that variousomissions, additions and modifications may be made to the methods andsystems described above without departing from the scope of theinvention. All such modifications and changes are intended to fallwithin the scope of the invention as illustrated by the appended claims.

1. A transmitter, comprising: at least one first multiplier configuredto weigh a first input signal with a first vector to form at least onefirst weighted signal; at least one second multiplier configured toweigh a second input signal with a second vector to form a secondweighted signal; at least one combiner configured to combine the atleast one first weighted signal with the at least one second weightedsignal to form a transmissible signal; and an antenna array configuredto transmit the transmissible signal; wherein the at least one firstmultiplier or the at least one second multiplier is configured tocompute the first vector or the second vector, respectively, usingeigenvalue decomposition; wherein the at least one first multiplierfurther comprises a first vector multiplier and a second vectormultiplier; wherein the first vector multiplier is configured to weighthe first input signal with a first transmitter vector to form a firsttransmitter vector weighted signal; and wherein the second vectormultiplier is configured to weigh the first input signal with a secondtransmitter vector to form a second transmitter vector weighted signal.2. The transmitter of claim 1, wherein the at least one secondmultiplier further comprises a third vector multiplier and a fourthvector multiplier; wherein the third vector multiplier is configured toweigh the second input signal with a third transmitter vector to form athird transmitter vector weighted signal; and wherein the fourth vectormultiplier is configured to weigh the second input signal with a fourthtransmitter vector to form a fourth transmitter vector weighted signal.3. The transmitter of claim 2, wherein the at least one combiner furthercomprises a first combiner and a second combiner; wherein the firstcombiner is configured to combine the first transmitter vector weightedsignal with the third transmitter vector weighted signal; and whereinthe second combiner is configured to combine the second transmittervector weighted signal with the fourth transmitter vector weightedsignal.
 4. The transmitter of claim 1, further comprising at least onewater-filling multiplier configured to weigh the first input signal orthe second input signal with a water-filling weight.
 5. A transmitter,comprising: at least one first multiplier means for weighing a firstinput signal with a first vector to form at least one first weightedsignal; at least one second multiplier means for weighing a second inputsignal with a second vector to form a second weighted signal; at leastone combiner means for combining the at least one first weighted signalwith the at least one second weighted signal to form a transmissiblesignal; and an antenna array means for transmitting the transmissiblesignal; wherein the at least one first multiplier means or the at leastone second multiplier means is configured to compute the first vector orthe second vector, respectively, using eigenvalue decomposition; whereinthe at least one first multiplier means further comprises a first vectormultiplier means and a second vector multiplier means; wherein the firstvector multiplier means is configured to weigh the first input signalwith a first transmitter vector to form a first transmitter vectorweighted signal; and wherein the second vector multiplier means isconfigured to weigh the first input signal with a second transmittervector to form a second transmitter vector weighted signal.
 6. Thetransmitter of claim 5, wherein the at least one second multiplier meansfurther comprises a third vector multiplier means and a fourth vectormultiplier means; wherein the third vector multiplier means isconfigured to weigh the second input signal with a third transmittervector to form a third transmitter vector weighted signal; and whereinthe fourth vector multiplier means is configured to weigh the secondinput signal with a fourth transmitter vector to form a fourthtransmitter vector weighted signal.
 7. The transmitter of claim 6,wherein the at least one combiner means further comprises a firstcombiner means and a second combiner means; wherein the first combinermeans is configured to combine the first transmitter vector weightedsignal with the third transmitter vector weighted signal; and whereinthe second combiner means is configured to combine the secondtransmitter vector weighted signal with the fourth transmitter vectorweighted signal.
 8. The transmitter of claim 5, further comprising atleast one water-filling multiplier means configured to weigh the firstinput signal or the second input signal with a water-filling weight. 9.A receiver, comprising: an array of receiver antennas configured toreceive a first transmitted signal and a second transmitted signal; atleast one first multiplier configured to weigh the first transmittedsignal with a first receiver vector to form at least one first weightedsignal; at least one second multiplier configured to weigh the secondtransmitted signal with a second receiver vector to form at least onesecond weighted signal; and at least one combiner configured to combinethe at least one first weighted signal with the at least one secondweighted signal to form an output signal; wherein the first receivervector or the second receiver vector are computed using eigenvaluedecomposition; wherein the at least one first multiplier furthercomprises a first vector multiplier and a second vector multiplier;wherein the first vector multiplier is configured to weigh the firsttransmitted signal with a first receiver vector to form a first receivervector weighted signal; and wherein the second vector multiplier isconfigured to weigh the first transmitted signal with a second receivervector to form a second receiver vector weighted signal.
 10. Thereceiver of claim 9, wherein the first transmitted signal is weightedwith a first transmitter vector; wherein the second transmitted signalis weighted with a second transmitter vector; and wherein the firsttransmitter vector or the second transmitter vector are computed usingeigenvalue decomposition.
 11. The receiver of claim 9, wherein the atleast one second multiplier further comprises a third vector multiplierand a fourth vector multiplier; wherein the third vector multiplier isconfigured to weigh the second transmitted signal with a third receivervector to form a third receiver vector weighted signal; and wherein thefourth vector multiplier is configured to weigh the second transmittedsignal with a fourth transmit vector to form a fourth receiver vectorweighted signal.
 12. The receiver of claim 11, wherein the at least onecombiner further comprises a first combiner and a second combiner;wherein the first combiner is configured to combine the first receivervector weighted signal with the third receiver vector weighted signal;and wherein the second combiner is configured to combine the secondreceiver vector weighted signal with the fourth receiver vector weightedsignal.
 13. The receiver of claim 9, wherein the first transmittedsignal or the second transmitted signal are respectively weighted with afirst water-filling vector or a second water-filling vector.
 14. Areceiver, comprising: antenna array means for receiving a firsttransmitted signal and a second transmitted signal; at least one firstmultiplier means for weighing the first transmitted signal with a firstreceiver vector to form at least one first weighted signal; at least onesecond multiplier means for weighing the second transmitted signal witha second receiver vector to form at least one second weighted signal;and at least one combiner means for combining the at least one firstweighted signal with the at least one second weighted signal to form anoutput signal; wherein the first receiver vector or the second receivervector are computed using eigenvalue decomposition; wherein the firsttransmitted signal is weighted with a first transmitter vector; whereinthe second transmitted signal is weighted with a second transmittervector; and wherein the first transmitter vector or the secondtransmitter vector are computed using eigenvalue decomposition.
 15. Thereceiver of claim 14, wherein the at least one first multiplier meansfurther comprises a first vector multiplier means and a second vectormultiplier means; wherein the first vector multiplier means isconfigured for weighing the first transmitted signal with a firstreceiver vector to form a first receiver vector weighted signal; andwherein the second vector multiplier means is configured for weighingthe first transmitted signal with a second receiver vector to form asecond receiver vector weighted signal.
 16. The receiver of claim 15,wherein the at least one second multiplier means further comprises athird vector multiplier means and a fourth vector multiplier means;wherein the third vector multiplier means is configured for weighing thesecond transmitted signal with a third receiver vector to form a thirdreceiver vector weighted signal; and wherein the fourth vectormultiplier means is configured for weighing the second transmittedsignal with a fourth transmit vector to form a fourth receiver vectorweighted signal.
 17. The receiver of claim 16, wherein the at least onecombiner means further comprises a first combiner means and a secondcombiner means; wherein the first combiner means is configured forcombining the first receiver vector weighted signal with the thirdreceiver vector weighted signal; and wherein the second combiner meansis configured for combining the second receiver vector weighted signalwith the fourth receiver vector weighted signal.
 18. The receiver ofclaim 14, wherein the first transmitted signal or the second transmittedsignal are respectively weighted with a first water-filling vector or asecond water-filling vector.